The ability to perform assignment inference depends on semantic discriminability of the colors, given the concepts in the encoding system. Semantic discriminability can be understood by analogy to perceptual discriminability. Perceptual discriminability concerns how well one can distinguish the appearance of different colors, whereas semantic discriminability concerns how well one can distinguish the meaning of different colors in the context of an encoding system [1]}, [2]}. In assignment inference, semantic discriminability is the degree to which one assignment has greater merit than the alternative assignment(s). For example, Fig. REF B shows color sets that differ in semantic discriminability for the concepts mango (M) and watermelon (W) (data from [1]}). The red and orange set (left) has high semantic discriminability because the W-red/M-orange assignment has far greater merit than the alternative. In contrast, the red and green set (right) has low semantic discriminability because the W-red/M-green assignment is only slightly better than the alternative. In their semantic discriminability theory, Mukherjee et al. [2]} specified constraints on the ability to design semantically discriminable color palettes for a given set of concepts.
